[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83785-en":3,"doc-seo-83785-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},83785,4398048950312,"Violet","https://ap-avatar.wpscdn.com/avatar/400002538284de19e3c?_k=1778320343897328908",8,"Research & Report","The Politics Attention Makes: Platform Media Logic and the Mediatization of Politics","Empirical research on social media and politics often treats platforms as systems that distribute messages, while mediatization shifts attention to production. This paper studies how platform attention pressures shape political expression by using attention price analysis to estimate differentiated attention returns for distinct expressive features. Using RoBERTa reward models trained on residualized engagement across X/Twitter, Bluesky, and Mastodon, the study compares how platforms reward rhetorical, emotional, epistemic, and relational characteristics of public communication.","The Politics Attention Makes: Platform Media Logic and the Mediatization of Politics  \nPetter Törnberg  \nInstitute for Logic, Language and Computation (ILLC), [University of Amsterdam. p.tornberg@uva.nl](University of Amsterdam. p.tornberg@uva.nl)  \nAbstract  \nEmpirical research on social media and politics has primarily treated platforms as distributive systems that expose users to particular messages. The mediatization literature, however, suggests shifting attention upstream: from circulation to production. Under intense competition for platform attention, political actors who depend on visibility face pressure to learn from recurrent differences in reach and engagement – shaping politics around platform media logic. This paper examines that production-side dimension of platforms political impact by introducing attention price analysis: an exploratory method for estimating the differentiated attention returns associated with forms of expression. Using RoBERTa reward models trained on residualized engagement across X/Twitter, Bluesky, and Mastodon, the analysis compares how platform environments reward rhetorical, emotional, epistemic, and relational features of public communication. The attention signal differs sharply across platforms and engagement actions.  \nX/Twitter sharing rewards antagonism while penalizing respect and nuance; Bluesky reposting favors neutral, lower-emotion language; and Mastodon boosts reward reasoning, nuance, compassion, and collective expression. Toxicity is rewarded across platforms, but in bounded and nonlinear ways. The findings suggest that moving from X/Twitter to less engagementoptimized alternatives such as Bluesky and Mastodon does not eliminate attention pressures, but it may reward less antagonistic and more deliberative forms of politics. The paper contributes a production-side approach to social media and politics by making one dimension of platform media logic empirically visible.  \nKeywords: attention economy; political communication; platformization; mediatization; engagement; amplification; reward models  \nIntroduction  \nThe dominant empirical account of social media and democracy is a story about distribution. Algorithms rank, feeds curate, networks cascade, and users encounter some messages rather than others. Platforms are seen as machines—or “prisms”(Bail, 2022)—for selecting what reaches audiences, and the central political question is what this exposure does to citizens: whether it polarizes, misinforms, mobilizes, or demobilizes them (Bakshy et al., 2015; Lorenz-Spreen et al., 2023; Tucker et al., 2018) . The focus on audience means that the democratic crisis associated with social media tends to be studied as primarily a crisis of the electorate (Törnberg, 2026a) . This literature is large, technically sophisticated, and substantively important. But its findings are often less straightforward than early diagnoses implied: large-scale interventions that changed social media use, feed ranking, or partisan exposure altered what people encountered but often produced surprisingly limited effects on political attitudes, affective polarization, or offline political behavior (Allcott et al., 2020; Guess et al., 2023; Nyhan et al., 2023) . Algorithms clearly shape what people see, but they do not straightforwardly determine what people believe, feel, or how they vote.  \nA long tradition in media and communication theory suggests that this distributional focus misses a key relationship between media and politics. Media do not merely transmit political messages; they reorganize the incentives and conditions under which messages are made, circulated, and rendered consequential (Couldry & Hepp, 2017; McLuhan, 1964; Postman, 1985). The mediatization literature has developed this argument most directly, showing how political actors, institutions, and movements adapt to media formats, rhythms, and evaluative criteria, until media logic becomes partly constitutive of how politics is organi","cbCaifFypWEQzu5e","https://ap.wps.com/l/cbCaifFypWEQzu5e","pdf",998724,1,29,"English","en",105,"# Abstract\n# Introduction\n## Distributional accounts of social media and democracy\n## Mediatization and production-side impacts\n## Attention as a quantified platform signal","[{\"question\":\"What does the paper propose by shifting from distribution to production in platform politics?\",\"answer\":\"It argues that political impacts should be studied upstream, focusing on how platform attention pressures shape what political actors learn to produce and how politics becomes organized and performed within platform media logic.\"},{\"question\":\"How is “attention price analysis” used in the study?\",\"answer\":\"The method estimates differentiated attention returns linked to forms of expression by comparing outcomes across platform environments, rather than treating engagement as a single undifferentiated signal.\"},{\"question\":\"How do different platforms reward different communication features?\",\"answer\":\"X/Twitter sharing rewards antagonism while penalizing respect and nuance; Bluesky reposting favors neutral, lower-emotion language; and Mastodon boosts rewards for reasoning, nuance, compassion, and collective expression.\"}]",1784190393,73,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"the-politics-attention-makes-platform-media-logic-and-the-mediatization-of-politics","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/the-politics-attention-makes-platform-media-logic-and-the-mediatization-of-politics/83785/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What does the paper propose by shifting from distribution to production in platform politics?","Question",{"text":74,"@type":75},"It argues that political impacts should be studied upstream, focusing on how platform attention pressures shape what political actors learn to produce and how politics becomes organized and performed within platform media logic.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"How is “attention price analysis” used in the study?",{"text":79,"@type":75},"The method estimates differentiated attention returns linked to forms of expression by comparing outcomes across platform environments, rather than treating engagement as a single undifferentiated signal.",{"name":81,"@type":72,"acceptedAnswer":82},"How do different platforms reward different communication features?",{"text":83,"@type":75},"X/Twitter sharing rewards antagonism while penalizing respect and nuance; 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